The goal of this research project is to demonstrate that genetic information can improve drug treatment regimens. The pharmacokinetic parameters for at least 4 different therapeutic agents will be measured across 11 inbred mouse strains. The strain-specific pharmacokinetic data will be evaluated using a haplotype-based computational method to identify the genetic loci responsible for the variation in pharmacokinetic responses. The computational predictions will be initially evaluated by correlation of allelic and gene expression patterns across inbred mouse strains, and with known information on the metabolism of these drugs. The effect that genetic alterations within the computationally predicted genes have on the metabolism of these drugs will be evaluated using in vitro and in vivo methodology. This experimental system will enable the factors effecting the metabolism of a drug to be efficiently and rapidly identified. Dosing regimens in mice based on information obtained from genotyping key loci will be developed and prospectively tested to evaluate the utility of genetically guided therapeutics. This model murine genetic system will assess the impact of genetically guided dose adjustment within a treatment population. If this approach is successfully applied to human therapy, it would have a significant impact on human health. To enable this, the following will be completed: 1) Polymorphisms in 150 murine genes effecting drug metabolism will be identified. 2) The pharmacokinetic profile (parent and metabolites) of coumadin, bleomycin, isoniazid and ritonavir will be measured in 11 inbred mouse strains. The genetic factors effecting this response will be computationally identified, and the effect that the predicted genes have on the metabolism of these drugs will be analyzed in vitro and in vivo. 3) One drug will be selected for evaluation of the utility of genetically guided dosing, and a clinical trial using genetically guided dosing will be performed in an experimental murine model.